
AFOSR/NSF Co-Sponsored Workshop on
Dynamic Data Driven Applications Systems (DDDAS) - Info-Symbiotic Systems
Arlington Hilton, Arlington, VA
August 30-31, 2010
Workshop Report
Previous Reports
Objectives
The Dynamic Data Driven Applications Systems (DDDAS) – Info-Symbiotic Systems workshop provides
a forum for creating concerted support for a comprehensive set of activities enabling new
capabilities engendered through the DDDAS concept.
The workshop features a stellar set of keynote speakers, and brings together a broad research
community from academe, industry, labs, and government to discuss wide set of topics on challenges
and opportunities, from fundamental research to efforts on comprehensive cyber-infrastructure
environments, relating to DDDAS.
Co-sponsored by AFOSR and NSF, and other agencies participation, the workshop will expand on
precedent research and programmatic activities, and emerging directions. A report, summarizing the
workshop presentations and discussions, will be produced and made broadly available.
Workshop Co-Chairs
- Prof. Craig Douglas, University of Wyoming
- Prof. Abani Patra, University of Buffalo
Cross-Agencies Committee
DoD/AFOSR
- Dir. Frederica Darema
- Dr. Bob Bonneau
- Dr. Fariba Fahroo
- Dr. David Stargel
- Dr. Kitt Reinhardt
NSF
- Dr. Lee Jameson (MPS)
- Dr. Ed Seidel (MPS)
- Dr. Manish Parashar (OCI)
- Dr. George Maracas (ENG)
- Dr. Tom Henderson (CISE)
- Dr. John Cherniavsky (EHR)
DoD/DTRA
DoD/ONR
DoD/ARL/CIS
NIH
- Dr. Milt Corn (NLM)
- Dr. Peter Lyster (NIGMS)
NASA
Presentation Slides
Preliminary Talks
- Dr. Dahm, U.S. Air Force "Technology Horizons"
Talk
- Dr. Ed Seidel, Data- and Compute-Driven Transformation of Science
Talk
- Dr. Frederica Darema, InfoSymbioticSystems - The Power of: Dynamic Data-Driven Application Systems (DDDAS)
Talk
- Prof. Abani Patra, AFOSR/NSF DDDAS Workshop Keystones
Talk
Plenary Talks
- Prof. J. Tinsley Oden,
A Dynamic Data-Driven System for Optimized Laser Treatment of Prostate Cancer
Talk
- Prof. Kelvin Droegemeir,
DDDAS Applied to High-Impact Local Weather: The LEAD Project
Talk
- Prof. Charbal Farhat and
Dr. John Michopoulos,
DDDAS for Material Characterization, Health Monitoring, and Critical Event Prediction of Complex Structures
- Prof. George Karniadakis,
Predictability and Uncertainty in DDDAS
Talk
- Prof. Santae Kim,
Is Life a Dynamic Data Driven DNA Application System?
Talk
- Prof. Patrick Jaillet,
Data-Driven Optimization: Illustrations, Opportunities, Some Results, Key Challenges
Talk
Secondary Talk
- Prof. J. Tinsley Oden, A Brief View of Verification, Validation, and Uncertainty Quantification
Talk
Working Group Charges
All WGs - Common and Overarching Issues
(Craig Douglas and Abani Patra)
All WGs should address the following common and
overarching issues:
- The scope of research challenges is clearly wide and in need of
fundamental advances. Why is now the right time for fostering this
kind of research?
- What are the Grand S&T Challenges in enabling DDDAS? What are
ongoing research advances can be used as leverage and springboard to
enable DDDAS?
(Each WG will address the research challenges
and opportunities)
- What kinds of processes, venues and mechanisms are optimal to
facilitate the multidisciplinary nature of the research needed in
enabling such capabilities?
- What past or existing initiatives can contribute, and what new
ones should be created to systematically support such efforts?
- What are the benefits of coordination and joint efforts across
agencies, nationally and in supporting synergistically such efforts?
- What kinds of connections with the industrial sector can be
beneficial? How can these be fostered effectively to focus research
efforts and expedite technology transfer?
- How these new research directions can be used to create exciting
new opportunities for undergraduate, graduate and postdoctoral
education and training?
- What novel and competitive workforce development opportunities
can ensue?
- What National and International critical challenges are
addressed through DDDAS capabilities?
WG1 - Algorithms and Data Assimilation
(George Biros and Janice Coen)
DDDAS environments require algorithms, mathematical
and statistical, both numeric and non-numeric, that have good
convergence properties under perturbations from streamed data into the
executing application. DDDAS goes beyond the traditional
data-assimilation approaches:
- What is the state-of-the-art and what are the challenges in the
applications algorithms to enable such capabilities for the
applications models/simulations?
- What algorithms? development is needed to enable application
algorithms tolerant to perturbations from "on-line" input data, and
with good stability properties?
- How can one select and incorporate dynamically appropriate
algorithms as the application requirements and data sets change in
the course of the simulation?
- What kinds of approaches, such as knowledge-based systems, can
be employed, and what interfaces and applications assists are needed
to allow such capabilities?
- What systems support is required to develop such environments?
- How do the existing methods and capabilities in the above need
to be advanced?
WG2 - Uncertainty Quantification and MultiScale Modeling
(Bani Mallick and Dongbin Xiu)
DDDAS environments entail application models that can
interface and dynamically interact with the measurement data systems
(archival, real-time data acquisition and control systems). Such
interaction entails dynamic application models and application
components, at runtime, as dictated by the streamed data, and can
include dynamic invocation of models at multiple scales? that is
"dynamic multi-scale". Models, experiments and observations are all
representations and discrete samples of behavior. Quantifying and
managing the outcomes of application systems (predictions, control
actions, ?) must account for these uncertainties. Such situations ensue
new and increased challenges, beyond the traditional multi-scale, and
uncertainty quantification considerations.
- What are the overall opportunities and challenges in DDDAS
applications modeling?
- What research and technologies are covered by the present
projects?
- As DDDAS requirements are expected to be dynamic, what are the
implied applications modeling technology advances that are need and
what?s the needed systems support?
- What is special if you have a multiscale/multiphysics system?
How do you do deal with multimodal data?
- What methodologies from the emerging field of UQ are applicable
here, and in particular in the case where models of other components
of the application are dynamically invoked? Conversely what new
developments are needed to enable the use of dynamic data and
simulations especially for complex systems? What are the issues in
data management, dynamic selection of application components,
mapping, interfaces for request and allocation of systems resources
so that quality of service is ensured for the applications?
- Provide applications examples that will benefit from the new
paradigm, existing and potential new applications, challenges in
developing such applications, multilevel and multimodal modeling,
composition of such complex applications, data management and
interfaces to experiments/field-data, computation, memory and I/O
requirements.
WG3 - Large and Heterogeneous Data from Distributed
Measurement & Control Systems
(Alok Chaturvedi and Adrian Sandhu)
DDDAS inherently involves large amounts of data that
can result from heterogeneous and distributed sources, collected in
differing time-scales and in different formats, and which need to be
preprocessed before automatically integrating them to the executing
applications that need use the new data.
- What is the state of the art in measurement systems and how are
they integrated in DDDAS, where measurements from sensors, other
instruments and data repositories are dynamically integrated with
the application modeling to improve the application modeling?
- Conversely, what is the state of the art in on-line application
control of the measurement instrument or process providing
opportunity to improve the measurement process, guide the design and
operational aspects of measurement instruments, and networks of
distributed heterogeneous sensors and networks of embedded
controllers?
- What are the methods that need to be developed to guide the
architecture of sets of sensors and other instruments thus improving
the effectiveness or efficiency of the measuring systems, and
networks of distributed heterogeneous sensors and networks of
embedded controllers?
- What are the challenges and opportunities in software and
hardware technologies to enable such dynamic interfaces to such
measurement and control systems, and their associated data sets?
What improvements in the methods are expected, how are they going to
be enabled?
- How the existing methods and capabilities in all the above need
to be advanced?
WG4 - Building an Infrastructure for DDDAS
(Gabrielle Allen and Shantenu Jha)
DDDAS integrates real-time sensor and other
measurement devices with special purpose data processing systems
together with the parts of the application that execute in larger
platforms and driving a seamless integration of stationary and mobile
devices together with large high-end platforms, entailing grids that go
beyond the present computational grids.
- What are the challenges in the infrastructure just described
above?
- What are the challenges and opportunities in software and
hardware technologies to enable such dynamic interfaces?
- What improvements in the measurement methods are expected and
how are they going to be enabled?
WG5 - Systems Software
(Srinidhi Varadarajan and Dinesh Mamocha)
Quality of service, program software environments,
data massaging, network security, and availability of common libraries
are all important to making a DDDAS work in a global manner.
- What is the state-of-the-art and what advances are needed in
algorithms and software and what new capabilities need to be
provided by the underlying systems and platforms on which these
applications execute, so that quality of service is ensured?
- What are the software challenges in the programming environments
for the development and runtime support, under conditions where the
underlying resources as well as the applications requirements might
be changing at execution time?
- What are the issues in data management, dynamic selection of
components, dynamic invocation of components, mapping to underlying
resources, interfaces for request, and allocation of systems
resources so that quality of service is ensured for the
applications?
- What are the additional capabilities that are needed in the
application support and systems management services?
- How can these be fostered effectively to focus research efforts
and expedite technology transfer?
Detailed Agenda
All Plenary Sessions will take place at the Arlington Hilton
(950 N. Stafford St.), Mezzanine Level.
Day 1, Monday, August 30, 2010
7:30 AM - 8:15 AM |
Registration and Refreshments |
8:15 AM - 9:00 AM |
Workshop Welcome
Introductory Remarks by AF, AFOSR, and NSF Leadership, and Co-Chairs
Dr. Frederica Darema, Director, AFOSR Directorate for
Mathematics, Information and Life Sciences
Dr. Ed Seidel, Assistant Director, NSF Directorate for
Mathematical and Physical Sciences
Dr. Werner Dahm, AF Chief Scientist
Prof. Craig C. Douglas, University of Wyoming, Workshop Co-Chair
Prof. Abani Patra, University of Buffalo, Workshop Co-Chair |
9:15 AM - 12:30 |
Plenary Presentations |
9:15 AM - 9:45 AM |
J. Tinsley Oden,
Univ. of Texas, Austin
A Dynamic Data-Driven System for Optimized Laser Treatment of
Prostate Cancer |
9:45 AM - 10:15 AM |
Prof.
Kelvin K. Droegemeier,
Univ. of Oklahoma
DDDAS Applied to High-Impact Local Weather: The LEAD Project |
10:15 AM - 10:30 AM |
Break |
10:30 AM - 11:00 AM |
Prof.
Charbel Farhat,
Stanford University and
Dr.
John Michopoulos,
Naval Research Laboratory
DDDAS for Material Characterization, Health Monitoring, and
Critical Event Prediction of Complex Structures |
11:00 AM - 11:30 AM |
Prof.
George E. Karniadakis,
Brown University
Predictability and Uncertainty in DDDAS |
11:30 AM - 12:00 PM |
Dr.
Sangtae Kim,
Morgridge Institute of Research
Is Life a Dynamic Data Driven DNA Application System? |
12:00 PM - 12:30 PM |
Prof.
Patrick Jaillet,
MIT
Data-Driven Optimization: Illustrations, Opportunities, Some
Results, Key Challenges |
12:30 PM - 1:30 PM |
Working Lunch |
1:30 PM - 3:30 PM |
Working Groups Session |
3:30 PM - 3:45 PM |
Break |
3:45 PM - 5:00 PM |
Discussion of Summary Presentations |
5:45 PM |
Adjourn for the day |
Day 2, Tuesday, August 31, 2010
8:15 AM - 8:30 AM |
Refreshments |
8:30 AM - 10:00 AM |
Working Groups Session |
10:00 AM - 10:15 AM |
Break |
10:15 AM - 12:00 PM |
Working Groups Session |
12:00 PM - 1:00 PM |
Working Lunch |
1:00 PM - 3:00 PM |
Working Groups Outbriefing |
3:00 PM - 3:30 PM |
Concluding Discussion |
3:30 PM |
Workshop Ends |
3:30 PM - 3:45 PM |
Break |
3:45 PM - 5:00 PM |
Meeting Only with Working Group Chairs and Organizers |
Day 3, Wednesday, September 1, 2010
Initial Write-up of the Report by the Working Group Chairs
and Organizers.
This website has been established and is maintained by Prof.
Craig C. Douglas.
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